Stimulus-dependent hemodynamic response timing across the human subcortical-cortical visual pathway identified through high spatiotemporal resolution 7T fMRI

The temporal specificity of BOLD fMRI is systematically related to anatomical and vascular features of the human brain

The ability to detect fast responses with functional MRI depends on the speed of hemodynamic responses to neural activity, because hemodynamic responses act as a temporal low-pass filter which blurs rapid changes. However, the shape and timing of hemodynamic responses are highly variable across the brain and across stimuli. This heterogeneity of responses implies that the temporal specificity of fMRI signals, or the ability of fMRI to preserve fast information, could also vary substantially across the cortex. In this work we investigated how local differences in hemodynamic response timing affect the temporal specificity of fMRI. We used ultra-high field (7T) fMRI at high spatiotemporal resolution, studying the primary visual cortex (V1) as a model area for investigation. We used visual stimuli oscillating at slow and fast frequencies to probe the temporal specificity of individual voxels. As expected, we identified substantial variability in temporal specificity, with some voxels preserving their responses to fast neural activity more effectively than others. We investigated which voxels had the highest temporal specificity, and tested whether voxel timing was related to anatomical and vascular features. We found that low temporal specificity is only weakly explained by the presence of large veins or cerebral cortical depth. Notably, however, temporal specificity depended strongly on a voxel's position along the anterior-posterior anatomical axis of V1, with voxels within the calcarine sulcus being capable of preserving close to 25% of their amplitude as the frequency of stimulation increased from 0.05Hz to 0.20Hz, and voxels nearest to the occipital pole preserving less than 18%. These results indicate that detection biases in high-resolution fMRI will depend on the anatomical and vascular features of the area being imaged, and that these biases will differ depending on the timing of the underlying neuronal activity. While we attribute this variance primarily to hemodynamic effects, neuronal nonlinearities may also influence response timing. Importantly, this spatial heterogeneity of temporal specificity suggests that it could be exploited to achieve higher specificity in some locations, and that tailored data analysis strategies may help improve the detection and interpretation of fast fMRI responses.

Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging - A Symposium Review

Advances in the spatiotemporal resolution and field-of-view of neuroimaging tools are driving mesoscale studies for translational neuroscience. On October 10, 2023, the Center for Mesoscale Mapping (CMM) at the Massachusetts General Hospital (MGH) Athinoula A. Martinos Center for Biomedical Imaging and the Massachusetts Institute of Technology (MIT) Health Sciences Technology based Neuroimaging Training Program (NTP) hosted a symposium exploring the state-of-the-art in this rapidly growing area of research. "Mesoscale Brain Mapping: Bridging Scales and Modalities in Neuroimaging" brought together researchers who use a broad range of imaging techniques to study brain structure and function at the convergence of the microscopic and macroscopic scales. The day-long event centered on areas in which the CMM has established expertise, including the development of emerging technologies and their application to clinical translational needs and basic neuroscience questions. The in-person symposium welcomed more than 150 attendees, including 57 faculty members, 61 postdoctoral fellows, 35 students, and four industry professionals, who represented institutions at the local, regional, and international levels. The symposium also served the training goals of both the CMM and the NTP. The event content, organization, and format were planned collaboratively by the faculty and trainees. Many CMM faculty presented or participated in a panel discussion, thus contributing to the dissemination of both the technologies they have developed under the auspices of the CMM and the findings they have obtained using those technologies. NTP trainees who benefited from the symposium included those who helped to organize the symposium and/or presented posters and gave "flash" oral presentations. In addition to gaining experience from presenting their work, they had opportunities throughout the day to engage in one-on-one discussions with visiting scientists and other faculty, potentially opening the door to future collaborations. The symposium presentations provided a deep exploration of the many technological advances enabling progress in structural and functional mesoscale brain imaging. Finally, students worked closely with the presenting faculty to develop this report summarizing the content of the symposium and putting it in the broader context of the current state of the field to share with the scientific community. We note that the references cited here include conference abstracts corresponding to the symposium poster presentations.

Displacement and functional ultrasound (fUS) imaging of displacement-guided focused ultrasound (FUS) neuromodulation in mice

Focused ultrasound (FUS) stimulation is a promising neuromodulation technique with the merits of non-invasiveness, high spatial resolution, and deep penetration depth. However, simultaneous imaging of FUS-induced brain tissue displacement and the subsequent effect of FUS stimulation on brain hemodynamics has proven challenging thus far. In addition, earlier studies lack in situ confirmation of targeting except for the magnetic resonance imaging-guided FUS system-based studies. The purpose of this study is 1) to introduce a fully ultrasonic approach to in situ target, modulate neuronal activity, and monitor the resultant neuromodulation effect by respectively leveraging displacement imaging, FUS, and functional ultrasound (fUS) imaging, and 2) to investigate FUS-evoked cerebral blood volume (CBV) response and the relationship between CBV and displacement. We performed displacement imaging on craniotomized mice to confirm the in situ targeting for neuromodulation site. We recorded hemodynamic responses evoked by FUS while fUS imaging revealed an ipsilateral CBV increase that peaks at 4 s post-FUS. We report a stronger hemodynamic activation in the subcortical region than cortical, showing good agreement with a brain elasticity map that can also be obtained using a similar methodology. We observed dose-dependent CBV responses with peak CBV, activated area, and correlation coefficient increasing with the ultrasonic dose. Furthermore, by mapping displacement and hemodynamic activation, we found that displacement colocalized and linearly correlated with CBV increase. The findings presented herein demonstrated that FUS evokes ipsilateral hemodynamic activation in cortical and subcortical depths while the evoked hemodynamic responses colocalize and correlate with FUS-induced displacement. We anticipate that our findings will help consolidate accurate targeting as well as shedding light on one of the mechanisms behind FUS modulation, i.e., how FUS mechanically displaces brain tissue affecting cerebral hemodynamics and thereby its associated connectivity.

Finding Pattern in the Noise: Persistent Implicit Statistical Knowledge Impacts the Processing of Unpredictable Stimuli

Humans can extract statistical regularities of the environment to predict upcoming events. Previous research recognized that implicitly acquired statistical knowledge remained persistent and continued to influence behavior even when the regularities were no longer present in the environment. Here, in an fMRI experiment, we investigated how the persistence of statistical knowledge is represented in the brain. Participants (n = 32) completed a visual, four-choice, RT task consisting of statistical regularities. Two types of blocks constantly alternated with one another throughout the task: predictable statistical regularities in one block type and unpredictable ones in the other. Participants were unaware of the statistical regularities and their changing distribution across the blocks. Yet, they acquired the statistical regularities and showed significant statistical knowledge at the behavioral level not only in the predictable blocks but also in the unpredictable ones, albeit to a smaller extent. Brain activity in a range of cortical and subcortical areas, including early visual cortex, the insula, the right inferior frontal gyrus, and the right globus pallidus/putamen contributed to the acquisition of statistical regularities. The right insula, inferior frontal gyrus, and hippocampus as well as the bilateral angular gyrus seemed to play a role in maintaining this statistical knowledge. The results altogether suggest that statistical knowledge could be exploited in a relevant, predictable context as well as transmitted to and retrieved in an irrelevant context without a predictable structure.

Neural correlates of response to joint attention in 2-to-5-year-olds in relation to ASD and social-communicative abilities: An fNIRS and behavioral study

Autism spectrum disorder (ASD) is associated with life-long challenges with social cognition, and one of its earliest and most common manifestations is atypical joint attention, which is a pivotal skill in social-cognitive and linguistic development. Early interventions for ASD children often focus on training initiation of joint attention (IJA) and response to joint attention bids (RJA), which are important for social communication and cognition. Here, we used functional near-infrared spectroscopy and behavioral measures to test typically developing (TD, n = 17) and ASD children (n = 18), to address the relationship between the neural correlates of RJA and social-communicative behavior. Group-level differences were present for RJA-specific activation over right temporal sites, where TD children showed higher levels of activation during RJA than ASD children, whereas the two groups did not differ in the control condition. Correlations between neural activation and behavioral traits suggest that, in ASD children, neural activation during RJA is related to the frequency of RJA behavior when the former is measured over left temporal sites, and to social affect symptoms when considered for right temporal sites. Possible implications of the evidenced correlations are discussed.

Functional ultrasound (fUS) imaging of displacement-guided focused ultrasound (FUS) neuromodulation in mice

Focused ultrasound (FUS) stimulation is a promising neuromodulation technique with the merits of non-invasiveness, high spatial resolution, and deep penetration depth. However, simultaneous imaging of FUS-induced brain tissue displacement and the subsequent effect of FUS stimulation on brain hemodynamics has proven challenging thus far. In addition, earlier studies lack in situ confirmation of targeting except for the magnetic resonance imaging-guided FUS system-based studies. The purpose of this study is 1) to introduce a fully ultrasonic approach to in situ target, modulate neuronal activity, and monitor the resultant neuromodulation effect by respectively leveraging displacement imaging, FUS, and functional ultrasound (fUS) imaging, and 2) to investigate FUS-evoked cerebral blood volume (CBV) response and the relationship between CBV and displacement. We performed displacement imaging on craniotomized mice to confirm the in targeting for neuromodulation site. We recorded hemodynamic responses evoked by FUS and fUS revealed an ipsilateral CBV increase that peaks at 4 s post-FUS. We saw a stronger hemodynamic activation in the subcortical region than cortical, showing good agreement with the brain elasticity map that can also be obtained using a similar methodology. We observed dose-dependent CBV response with peak CBV, activated area, and correlation coefficient increasing with ultrasonic dose. Furthermore, by mapping displacement and hemodynamic activation, we found that displacement colocalizes and linearly correlates with CBV increase. The findings presented herein demonstrated that FUS evokes ipsilateral hemodynamic activation in cortical and subcortical depths and the evoked hemodynamic responses colocalized and correlate with FUS-induced displacement. We anticipate that our findings will help consolidate accurate targeting as well as an understanding of how FUS displaces brain tissue and affects cerebral hemodynamics.

Human subcortical pathways automatically detect collision trajectory without attention and awareness

Detecting imminent collisions is essential for survival. Here, we used high-resolution fMRI at 7 Tesla to investigate the role of attention and consciousness for detecting collision trajectory in human subcortical pathways. Healthy participants can precisely discriminate collision from near-miss trajectory of an approaching object, with pupil size change reflecting collision sensitivity. Subcortical pathways from the superior colliculus (SC) to the ventromedial pulvinar (vmPul) and ventral tegmental area (VTA) exhibited collision-sensitive responses even when participants were not paying attention to the looming stimuli. For hemianopic patients with unilateral lesions of the geniculostriate pathway, the ipsilesional SC and VTA showed significant activation to collision stimuli in their scotoma. Furthermore, stronger SC responses predicted better behavioral performance in collision detection even in the absence of awareness. Therefore, human tectofugal pathways could automatically detect collision trajectories without the observers' attention to and awareness of looming stimuli, supporting "blindsight" detection of impending visual threats.

Longitudinal changes in human supraspinal processing after RIII-feedback training to improve descending pain inhibition

The human body has the ability to influence its sensation of pain by modifying the transfer of nociceptive information at the spinal level. This modulation, known as descending pain inhibition, is known to originate supraspinally and can be activated by a variety of ways including positive mental imagery. However, its exact mechanisms remain unknown. We investigated, using a longitudinal fMRI design, the brain activity leading up and in response to painful electrical stimulation when applying positive mental imagery before and after undergoing a previously established RIII-feedback paradigm. Time course analysis of the time preceding painful stimulation shows increased haemodynamic activity during the application of the strategy in the PFC, ACC, insula, thalamus, and hypothalamus. Time course analysis of the reaction to painful stimulation shows decreased reaction post-training in brainstem and thalamus, as well as the insula and dorsolateral PFC. Our work suggests that feedback training increases activity in areas involved in pain inhibition, while simultaneously decreasing the reaction to painful stimuli in brain areas related to pain processing, which points to an activation of decreased spinal nociception. We further suggest that the insula and the thalamus may play a more important role in pain modulation than previously assumed.

Comparison of hemodynamic response functions obtained from resting-state functional MRI and invasive electrophysiological recordings in rats

Resting-state functional MRI (rs-fMRI) is a popular technology that has enriched our understanding of brain and spinal cord functioning, including how different regions communicate (connectivity). But fMRI is an indirect measure of neural activity capturing blood hemodynamics. The hemodynamic response function (HRF) interfaces between the unmeasured neural activity and measured fMRI time series. The HRF is variable across brain regions and individuals, and is modulated by non-neural factors. Ignoring this HRF variability causes errors in FC estimates. Hence, it is crucial to reliably estimate the HRF from rs-fMRI data. Robust techniques have emerged to estimate the HRF from fMRI time series. Although such techniques have been validated non-invasively using simulated and empirical fMRI data, thorough invasive validation using simultaneous electrophysiological recordings, the gold standard, has been elusive. This report addresses this gap in the literature by comparing HRFs derived from invasive intracranial electroencephalogram recordings with HRFs estimated from simultaneously acquired fMRI data in six epileptic rats. We found that the HRF shape parameters (HRF amplitude, latency and width) were not significantly different (p>0.05) between ground truth and estimated HRFs. In the single pathological region, the HRF width was marginally significantly different (p=0.03). Our study provides preliminary invasive validation for the efficacy of the HRF estimation technique in reliably estimating the HRF non-invasively from rs-fMRI data directly. This has a notable impact on rs-fMRI connectivity studies, and we recommend that HRF deconvolution be performed to minimize HRF variability and improve connectivity estimates.

Resting-state fMRI signals contain spectral signatures of local hemodynamic response timing

Functional magnetic resonance imaging (fMRI) has proven to be a powerful tool for noninvasively measuring human brain activity; yet, thus far, fMRI has been relatively limited in its temporal resolution. A key challenge is understanding the relationship between neural activity and the blood-oxygenation-level-dependent (BOLD) signal obtained from fMRI, generally modeled by the hemodynamic response function (HRF). The timing of the HRF varies across the brain and individuals, confounding our ability to make inferences about the timing of the underlying neural processes. Here, we show that resting-state fMRI signals contain information about HRF temporal dynamics that can be leveraged to understand and characterize variations in HRF timing across both cortical and subcortical regions. We found that the frequency spectrum of resting-state fMRI signals significantly differs between voxels with fast versus slow HRFs in human visual cortex. These spectral differences extended to subcortex as well, revealing significantly faster hemodynamic timing in the lateral geniculate nucleus of the thalamus. Ultimately, our results demonstrate that the temporal properties of the HRF impact the spectral content of resting-state fMRI signals and enable voxel-wise characterization of relative hemodynamic response timing. Furthermore, our results show that caution should be used in studies of resting-state fMRI spectral properties, because differences in fMRI frequency content can arise from purely vascular origins. This finding provides new insight into the temporal properties of fMRI signals across voxels, which is crucial for accurate fMRI analyses, and enhances the ability of fast fMRI to identify and track fast neural dynamics.

The confound of hemodynamic response function variability in human resting-state functional MRI studies

Functional magnetic resonance imaging (fMRI) is an indirect measure of neural activity with the hemodynamic response function (HRF) coupling it with unmeasured neural activity. The HRF, modulated by several non-neural factors, is variable across brain regions, individuals and populations. Yet, a majority of human resting-state fMRI connectivity studies continue to assume a non-variable HRF. In this article, with supportive prior evidence, we argue that HRF variability cannot be ignored as it substantially confounds within-subject connectivity estimates and between-subjects connectivity group differences. We also discuss its clinical relevance with connectivity impairments confounded by HRF aberrations in several disorders. We present limited data on HRF differences between women and men, which resulted in a 15.4% median error in functional connectivity estimates in a group-level comparison. We also discuss the implications of HRF variability for fMRI studies in the spinal cord. There is a need for more dialogue within the community on the HRF confound, and we hope that our article is a catalyst in the process.

The impact of the human thalamus on brain-wide information processing

The thalamus is a small, bilateral structure in the diencephalon that integrates signals from many areas of the CNS. This critical anatomical position allows the thalamus to influence whole-brain activity and adaptive behaviour. However, traditional research paradigms have struggled to attribute specific functions to the thalamus, and it has remained understudied in the human neuroimaging literature. Recent advances in analytical techniques and increased accessibility to large, high-quality data sets have brought forth a series of studies and findings that (re-)establish the thalamus as a core region of interest in human cognitive neuroscience, a field that otherwise remains cortico-centric. In this Perspective, we argue that using whole-brain neuroimaging approaches to investigate the thalamus and its interaction with the rest of the brain is key for understanding systems-level control of information processing. To this end, we highlight the role of the thalamus in shaping a range of functional signatures, including evoked activity, interregional connectivity, network topology and neuronal variability, both at rest and during the performance of cognitive tasks.

Pupil size reflects activation of subcortical ascending arousal system nuclei during rest

Neuromodulatory nuclei that are part of the ascending arousal system (AAS) play a crucial role in regulating cortical state and optimizing task performance. Pupil diameter, under constant luminance conditions, is increasingly used as an index of activity of these AAS nuclei. Indeed, task-based functional imaging studies in humans have begun to provide evidence of stimulus-driven pupil-AAS coupling. However, whether there is such a tight pupil-AAS coupling during rest is not clear. To address this question, we examined simultaneously acquired resting-state fMRI and pupil-size data from 74 participants, focusing on six AAS nuclei: the locus coeruleus, ventral tegmental area, substantia nigra, dorsal and median raphe nuclei, and cholinergic basal forebrain. Activation in all six AAS nuclei was optimally correlated with pupil size at 0-2 s lags, suggesting that spontaneous pupil changes were almost immediately followed by corresponding BOLD-signal changes in the AAS. These results suggest that spontaneous changes in pupil size that occur during states of rest can be used as a noninvasive general index of activity in AAS nuclei. Importantly, the nature of pupil-AAS coupling during rest appears to be vastly different from the relatively slow canonical hemodynamic response function that has been used to characterize task-related pupil-AAS coupling.

Cognitive and affective interaction with somatosensory afference in acupuncture-a specific brain response to compound stimulus

Introduction

Acupuncture is a clinical intervention consisting of multiple stimulus components, including somatosensory stimulation and manipulation of therapeutic context. Existing findings in neuroscience consolidated cognitive modulation to somatosensory afferent process, which could differ from placebo mechanism in brain. Here, we aimed to identify intrinsic process of brain interactions induced by compound stimulus of acupuncture treatment.

Methods

To separately and comprehensively investigate somatosensory afferent and cognitive/affective processes in brain, we implemented a novel experimental protocol of contextual manipulation with somatosensory stimulation (real acupuncture: REAL) and only contextual manipulation (phantom acupuncture: PHNT) for fMRI scan, and conducted independent component (IC)-wise assessment with the concatenated fMRI data.

Results

By our double (experimentally and analytically) dissociation, two ICs (CA1: executive control, CA2: goal-directed sensory process) for cognitive/affective modulation (associated with both REAL and PHNT) and other two ICs (SA1: interoceptive attention and motor-reaction, SA2: somatosensory representation) for somatosensory afference (associated with only REAL) were identified. Moreover, coupling between SA1 and SA2 was associated with a decreased heart rate during stimulation, whereas CA1 was associated with a delayed heart rate decrease post-stimulation. Furthermore, partial correlation network for these components demonstrated a bi-directional interaction between CA1 and SA1/SA2, suggesting the cognitive modulation to somatosensory process. The expectation for the treatment negatively affected CA1 but positively affected SA1 in REAL, whereas the expectation positively affected CA1 in PHNT.

Discussion

These specific cognitive-somatosensory interaction in REAL were differed from vicarious sensation mechanism in PHNT; and might be associated with a characteristic of acupuncture, which induces voluntary attention for interoception. Our findings on brain interactions in acupuncture treatment elucidated the underlying brain mechanisms for compound stimulus of somatosensory afferent and therapeutic contextual manipulation, which might be a specific response to acupuncture.

Neural activity induced by sensory stimulation can drive large-scale cerebrospinal fluid flow during wakefulness in humans

Cerebrospinal fluid (CSF) flow maintains healthy brain homeostasis, facilitating solute transport and the exchange of brain waste products. CSF flow is thus important for brain health, but the mechanisms that control its large-scale movement through the ventricles are not well understood. While it is well established that CSF flow is modulated by respiratory and cardiovascular dynamics, recent work has also demonstrated that neural activity is coupled to large waves of CSF flow in the ventricles during sleep. To test whether the temporal coupling between neural activity and CSF flow is in part due to a causal relationship, we investigated whether CSF flow could be induced by driving neural activity with intense visual stimulation. We manipulated neural activity with a flickering checkerboard visual stimulus and found that we could drive macroscopic CSF flow in the human brain. The timing and amplitude of CSF flow was matched to the visually evoked hemodynamic responses, suggesting neural activity can modulate CSF flow via neurovascular coupling. These results demonstrate that neural activity can contribute to driving CSF flow in the human brain and that the temporal dynamics of neurovascular coupling can explain this effect.

Resting-state fMRI signals contain spectral signatures of local hemodynamic response timing

Functional magnetic resonance imaging (fMRI) has proven to be a powerful tool for noninvasively measuring human brain activity; yet, thus far, fMRI has been relatively limited in its temporal resolution. A key challenge is understanding the relationship between neural activity and the blood-oxygenation-level-dependent (BOLD) signal obtained from fMRI, generally modeled by the hemodynamic response function (HRF). The timing of the HRF varies across the brain and individuals, confounding our ability to make inferences about the timing of the underlying neural processes. Here we show that resting-state fMRI signals contain information about HRF temporal dynamics that can be leveraged to understand and characterize variations in HRF timing across both cortical and subcortical regions. We found that the frequency spectrum of resting-state fMRI signals significantly differs between voxels with fast versus slow HRFs in human visual cortex. These spectral differences extended to subcortex as well, revealing significantly faster hemodynamic timing in the lateral geniculate nucleus of the thalamus. Ultimately, our results demonstrate that the temporal properties of the HRF impact the spectral content of resting-state fMRI signals and enable voxel-wise characterization of relative hemodynamic response timing. Furthermore, our results show that caution should be used in studies of resting-state fMRI spectral properties, as differences can arise from purely vascular origins. This finding provides new insight into the temporal properties of fMRI signals across voxels, which is crucial for accurate fMRI analyses, and enhances the ability of fast fMRI to identify and track fast neural dynamics.

State-of-the-art imaging of neuromodulatory subcortical systems in aging and Alzheimer's disease: Challenges and opportunities

Primary prevention trials have shifted their focus to the earliest stages of Alzheimer's disease (AD). Autopsy data indicates that the neuromodulatory subcortical systems' (NSS) nuclei are specifically vulnerable to initial tau pathology, indicating that these nuclei hold great promise for early detection of AD in the context of the aging brain. The increasing availability of new imaging methods, ultra-high field scanners, new radioligands, and routine deep brain stimulation implants has led to a growing number of NSS neuroimaging studies on aging and neurodegeneration. Here, we review findings of current state-of-the-art imaging studies assessing the structure, function, and molecular changes of these nuclei during aging and AD. Furthermore, we identify the challenges associated with these imaging methods, important pathophysiologic gaps to fill for the AD NSS neuroimaging field, and provide future directions to improve our assessment, understanding, and clinical use of in vivo imaging of the NSS.

Deconvolution of the Functional Ultrasound Response in the Mouse Visual Pathway Using Block-Term Decomposition

Functional ultrasound (fUS) indirectly measures brain activity by detecting changes in cerebral blood volume following neural activation. Conventional approaches model such functional neuroimaging data as the convolution between an impulse response, known as the hemodynamic response function (HRF), and a binarized representation of the input signal based on the stimulus onsets, the so-called experimental paradigm (EP). However, the EP may not characterize the whole complexity of the activity-inducing signals that evoke the hemodynamic changes. Furthermore, the HRF is known to vary across brain areas and stimuli. To achieve an adaptable framework that can capture such dynamics of the brain function, we model the multivariate fUS time-series as convolutive mixtures and apply block-term decomposition on a set of lagged fUS autocorrelation matrices, revealing both the region-specific HRFs and the source signals that induce the hemodynamic responses. We test our approach on two mouse-based fUS experiments. In the first experiment, we present a single type of visual stimulus to the mouse, and deconvolve the fUS signal measured within the mouse brain's lateral geniculate nucleus, superior colliculus and visual cortex. We show that the proposed method is able to recover back the time instants at which the stimulus was displayed, and we validate the estimated region-specific HRFs based on prior studies. In the second experiment, we alter the location of the visual stimulus displayed to the mouse, and aim at differentiating the various stimulus locations over time by identifying them as separate sources.

Characterization of the blood oxygen level dependent hemodynamic response function in human subcortical regions with high spatiotemporal resolution

Subcortical brain regions are absolutely essential for normal human function. These phylogenetically early brain regions play critical roles in human behaviors such as the orientation of attention, arousal, and the modulation of sensory signals to cerebral cortex. Despite the critical health importance of subcortical brain regions, there has been a dearth of research on their neurovascular responses. Blood oxygen level dependent (BOLD) functional MRI (fMRI) experiments can help fill this gap in our understanding. The BOLD hemodynamic response function (HRF) evoked by brief (<4 s) neural activation is crucial for the interpretation of fMRI results because linear analysis between neural activity and the BOLD response relies on the HRF. Moreover, the HRF is a consequence of underlying local blood flow and oxygen metabolism, so characterization of the HRF enables understanding of neurovascular and neurometabolic coupling. We measured the subcortical HRF at 9.4T and 3T with high spatiotemporal resolution using protocols that enabled reliable delineation of HRFs in individual subjects. These results were compared with the HRF in visual cortex. The HRF was faster in subcortical regions than cortical regions at both field strengths. There was no significant undershoot in subcortical areas while there was a significant post-stimulus undershoot that was tightly coupled with its peak amplitude in cortex. The different BOLD temporal dynamics indicate different vascular dynamics and neurometabolic responses between cortex and subcortical nuclei.

It's about time: Linking dynamical systems with human neuroimaging to understand the brain

Most human neuroscience research to date has focused on statistical approaches that describe stationary patterns of localized neural activity or blood flow. While these patterns are often interpreted in light of dynamic, information-processing concepts, the static, local, and inferential nature of the statistical approach makes it challenging to directly link neuroimaging results to plausible underlying neural mechanisms. Here, we argue that dynamical systems theory provides the crucial mechanistic framework for characterizing both the brain's time-varying quality and its partial stability in the face of perturbations, and hence, that this perspective can have a profound impact on the interpretation of human neuroimaging results and their relationship with behavior. After briefly reviewing some key terminology, we identify three key ways in which neuroimaging analyses can embrace a dynamical systems perspective: by shifting from a local to a more global perspective, by focusing on dynamics instead of static snapshots of neural activity, and by embracing modeling approaches that map neural dynamics using "forward" models. Through this approach, we envisage ample opportunities for neuroimaging researchers to enrich their understanding of the dynamic neural mechanisms that support a wide array of brain functions, both in health and in the setting of psychopathology.

A temporal sequence of thalamic activity unfolds at transitions in behavioral arousal state

Awakening from sleep reflects a profound transformation in neural activity and behavior. The thalamus is a key controller of arousal state, but whether its diverse nuclei exhibit coordinated or distinct activity at transitions in behavioral arousal state is unknown. Using fast fMRI at ultra-high field (7 Tesla), we measured sub-second activity across thalamocortical networks and within nine thalamic nuclei to delineate these dynamics during spontaneous transitions in behavioral arousal state. We discovered a stereotyped sequence of activity across thalamic nuclei and cingulate cortex that preceded behavioral arousal after a period of inactivity, followed by widespread deactivation. These thalamic dynamics were linked to whether participants subsequently fell back into unresponsiveness, with unified thalamic activation reflecting maintenance of behavior. These results provide an outline of the complex interactions across thalamocortical circuits that orchestrate behavioral arousal state transitions, and additionally, demonstrate that fast fMRI can resolve sub-second subcortical dynamics in the human brain.

Event-recurring multiband SWIFT functional MRI with 200-ms temporal resolution during deep brain stimulation and isoflurane-induced burst suppression in rat

PURPOSE

To develop a high temporal resolution functional MRI method for tracking repeating events in the brain.

METHODS

We developed a novel functional MRI method using multiband sweep imaging with Fourier transformation (SWIFT), termed event-recurring SWIFT (EVER-SWIFT). The method is able to image similar repeating events with subsecond temporal resolution. Here, we demonstrate the use of EVER-SWIFT for detecting functional MRI responses during deep brain stimulation of the medial septal nucleus and during spontaneous isoflurane-induced burst suppression in the rat brain at 9.4 T with 200-ms temporal resolution.

RESULTS

The EVER-SWIFT approach showed that the shapes and time-to-peak values of the response curves to deep brain stimulation significantly differed between downstream brain regions connected to the medial septal nucleus, resembling findings obtained with traditional 2-second temporal resolution. In contrast, EVER-SWIFT allowed for detailed temporal measurement of a spontaneous isoflurane-induced bursting activity pattern, which was not achieved with traditional temporal resolution.

CONCLUSION

The EVER-SWIFT technique enables subsecond 3D imaging of both stimulated and spontaneously recurring brain activities, and thus holds great potential for studying the mechanisms of neuromodulation and spontaneous brain activity.

Task-related hemodynamic responses in human early visual cortex are modulated by task difficulty and behavioral performance

Early visual cortex exhibits widespread hemodynamic responses in the absence of visual stimulation, which are entrained to the timing of a task and not predicted by local spiking or local field potential. Such task-related responses (TRRs) covary with reward magnitude and physiological signatures of arousal. It is unknown, however, if TRRs change on a trial-to-trial basis according to behavioral performance and task difficulty. If so, this would suggest that TRRs reflect arousal on a trial-to-trial timescale and covary with critical task and behavioral variables. We measured functional magnetic resonance imaging blood-oxygen-level-dependent (fMRI-BOLD) responses in the early visual cortex of human observers performing an orientation discrimination task consisting of separate easy and hard runs of trials. Stimuli were presented in a small portion of one hemifield, but the fMRI response was measured in the ipsilateral hemisphere, far from the stimulus representation and focus of spatial attention. TRRs scaled in amplitude with task difficulty, behavioral accuracy, reaction time, and lapses across trials. These modulations were not explained by the influence of respiration, cardiac activity, or head movement on the fMRI signal. Similar modulations with task difficulty and behavior were observed in pupil size. These results suggest that TRRs reflect arousal and behavior on the timescale of individual trials.

Short-term plasticity in the human visual thalamus

While there is evidence that the visual cortex retains a potential for plasticity in adulthood, less is known about the subcortical stages of visual processing. Here we asked whether short-term ocular dominance plasticity affects the human visual thalamus. We addressed this question in normally sighted adult humans, using ultra-high field (7T) magnetic resonance imaging combined with the paradigm of short-term monocular deprivation. With this approach, we previously demonstrated transient shifts of perceptual eye dominance and ocular dominance in visual cortex (Binda et al., 2018). Here we report evidence for short-term plasticity in the ventral division of the pulvinar (vPulv), where the deprived eye representation was enhanced over the non-deprived eye. This ventral-pulvinar plasticity was similar as previously seen in visual cortex and it was correlated with the ocular dominance shift measured behaviorally. In contrast, there was no effect of monocular deprivation in two adjacent thalamic regions: dorsal pulvinar (dPulv), and Lateral Geniculate Nucleus (LGN). We conclude that the visual thalamus retains potential for short-term plasticity in adulthood; the plasticity effect differs across thalamic subregions, possibly reflecting differences in their cortico-fugal connectivity.

Weak Task Synchronization of Default Mode Network in Task Based Paradigms

The brains Default mode network (DMN) is generally characterized by brain areas that gets deactivated upon the presentation of a wide variety of externally focused, attention demanding tasks. These areas also exhibit significant intra-DMN functional connectivity and significant negative functional connectivity with other brain areas, especially with attention networks, in both resting state and task conditions. Therefore, the DMN has been hypothesized to be involved in internally directed cognitive activities such as autobiographical recall of the past, future planning and mind wandering. Recent research has discovered the role of bottom-up attention in modulating the behaviour of DMN. We hypothesize that the de-engagement of the DMN regions upon the presentation of an externally-focused attention-demanding stimulus may not be strictly stimulus locked and may exhibit significant trial-to-trial as well as subject-to-subject variability. Due to the involvement of frontoparietal control network in modulating the anticorrelations between DMN and dorsal attention network (DAN), we expect the DMN regions to have lower inter-trial and inter-subject synchronization in their fMRI BOLD responses as compared to the bottom-up early-sensory task-positive regions. To test this hypothesis, we designed new statistical methods called Inter Trial Temporal Synchronization Analysis (IT-TSA) and Inter Subject TSA (IS-TSA) to analyse variability across trials and subjects respectively. We analysed four publicly available datasets (total 223 subjects) across seven tasks related to different cognitive modalities and found out that there is significantly low stimulus-locked synchronization across trials and subjects in the DMN regions as compared to early sensory task positive regions. Our study challenges the understanding of DMN as a strictly task-negative region and supports the recent findings that DMN acts as an active component associated with intrinsic processing which deactivates differentially and non-linearly across trials and subjects in the presence of extrinsic processes.

Using high spatial resolution fMRI to understand representation in the auditory network

Following rapid methodological advances, ultra-high field (UHF) functional and anatomical magnetic resonance imaging (MRI) has been repeatedly and successfully used for the investigation of the human auditory system in recent years. Here, we review this work and argue that UHF MRI is uniquely suited to shed light on how sounds are represented throughout the network of auditory brain regions. That is, the provided gain in spatial resolution at UHF can be used to study the functional role of the small subcortical auditory processing stages and details of cortical processing. Further, by combining high spatial resolution with the versatility of MRI contrasts, UHF MRI has the potential to localize the primary auditory cortex in individual hemispheres. This is a prerequisite to study how sound representation in higher-level auditory cortex evolves from that in early (primary) auditory cortex. Finally, the access to independent signals across auditory cortical depths, as afforded by UHF, may reveal the computations that underlie the emergence of an abstract, categorical sound representation based on low-level acoustic feature processing. Efforts on these research topics are underway. Here we discuss promises as well as challenges that come with studying these research questions using UHF MRI, and provide a future outlook.

Imaging faster neural dynamics with fast fMRI: A need for updated models of the hemodynamic response

Fast fMRI enables the detection of neural dynamics over timescales of hundreds of milliseconds, suggesting it may provide a new avenue for studying subsecond neural processes in the human brain. The magnitudes of these fast fMRI dynamics are far greater than predicted by canonical models of the hemodynamic response. Several studies have established nonlinear properties of the hemodynamic response that have significant implications for fast fMRI. We first review nonlinear properties of the hemodynamic response function that may underlie fast fMRI signals. We then illustrate the breakdown of canonical hemodynamic response models in the context of fast neural dynamics. We will then argue that the canonical hemodynamic response function is not likely to reflect the BOLD response to neuronal activity driven by sparse or naturalistic stimuli or perhaps to spontaneous neuronal fluctuations in the resting state. These properties suggest that fast fMRI is capable of tracking surprisingly fast neuronal dynamics, and we discuss the neuroscientific questions that could be addressed using this approach.

Investigating mechanisms of fast BOLD responses: The effects of stimulus intensity and of spatial heterogeneity of hemodynamics

Recent studies have demonstrated that fast fMRI can track neural activity well above the temporal limit predicted by the canonical hemodynamic response model. While these findings are promising, the biophysical mechanisms underlying these fast fMRI phenomena remain underexplored. In this study, we discuss two aspects of the hemodynamic response, complementary to several existing hypotheses, that can accommodate faster fMRI dynamics beyond those predicted by the canonical model. First, we demonstrate, using both visual and somatosensory paradigms, that the timing and shape of hemodynamic response functions (HRFs) vary across graded levels of stimulus intensity-with lower-intensity stimulation eliciting faster and narrower HRFs. Second, we show that as the spatial resolution of fMRI increases, voxel-wise HRFs begin to deviate from the canonical model, with a considerable portion of voxels exhibiting faster temporal dynamics than predicted by the canonical HRF. Collectively, both stimulus/task intensity and image resolution can affect the sensitivity of fMRI to fast brain activity, which may partly explain recent observations of fast fMRI signals. It is further noteworthy that, while the present investigations focus on fast neural responses, our findings suggest that a revised hemodynamic model may benefit the many fMRI studies using paradigms with wide ranges of contrast levels (e.g., resting or naturalistic conditions) or with modern, high-resolution MR acquisitions.

Most favorable stimulation duration in the sensorimotor cortex for fNIRS-based BCI

One of the primary objectives of the brain-computer interface (BCI) is to obtain a command with higher classification accuracy within the shortest possible time duration. Therefore, this study evaluates several stimulation durations to propose a duration that can yield the highest classification accuracy. Furthermore, this study aims to address the inherent delay in the hemodynamic responses (HRs) for the command generation time. To this end, HRs in the sensorimotor cortex were evaluated for the functional near-infrared spectroscopy (fNIRS)-based BCI. To evoke brain activity, right-hand-index finger poking and tapping tasks were used. In this study, six different stimulation durations (i.e., 1, 3, 5, 7, 10, and 15 s) were tested on 10 healthy male subjects. Upon stimulation, different temporal features and multiple time windows were utilized to extract temporal features. The extracted features were then classified using linear discriminant analysis. The classification results using the main HR showed that a 5 s stimulation duration could yield the highest classification accuracy, i.e., 74%, with a combination of the mean and maximum value features. However, the results were not significantly different from the classification accuracy obtained using the 15 s stimulation. To further validate the results, a classification using the initial dip was performed. The results obtained endorsed the finding with an average classification accuracy of 73.5% using the features of minimum peak and skewness in the 5 s window. The results based on classification using the initial dip for 5 s were significantly different from all other tested stimulation durations (p < 0.05) for all feature combinations. Moreover, from the visual inspection of the HRs, it is observed that the initial dip occurred as soon as the task started, but the main HR had a delay of more than 2 s. Another interesting finding is that impulsive stimulation in the sensorimotor cortex can result in the generation of a clearer initial dip phenomenon. The results reveal that the command for the fNIRS-based BCI can be generated using the 5 s stimulation duration. In conclusion, the use of the initial dip can reduce the time taken for the generation of commands and can be used to achieve a higher classification accuracy for the fNIRS-BCI within a 5 s task duration rather than relying on longer durations.

Statistical power or more precise insights into neuro-temporal dynamics? Assessing the benefits of rapid temporal sampling in fMRI

Functional magnetic resonance imaging (fMRI), a non-invasive and widely used human neuroimaging method, is most known for its spatial precision. However, there is a growing interest in its temporal sensitivity. This is despite the temporal blurring of neuronal events by the blood oxygen level dependent (BOLD) signal, the peak of which lags neuronal firing by 4-6 seconds. Given this, the goal of this review is to answer a seemingly simple question - "What are the benefits of increased temporal sampling for fMRI?". To answer this, we have combined fMRI data collected at multiple temporal scales, from 323 to 1000 milliseconds, with a review of both historical and contemporary temporal literature. After a brief discussion of technological developments that have rekindled interest in temporal research, we next consider the potential statistical and methodological benefits. Most importantly, we explore how fast fMRI can uncover previously unobserved neuro-temporal dynamics - effects that are entirely missed when sampling at conventional 1 to 2 second rates. With the intrinsic link between space and time in fMRI, this temporal renaissance also delivers improvements in spatial precision. Far from producing only statistical gains, the array of benefits suggest that the continued temporal work is worth the effort.

MRI with ultrahigh field strength and high-performance gradients: challenges and opportunities for clinical neuroimaging at 7 T and beyond

Research in ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology has provided enormous gains in sensitivity, resolution, and contrast for neuroimaging. This article provides an overview of the technical advantages and challenges of performing clinical neuroimaging studies at ultrahigh magnetic field strength combined with ultrahigh and ultrafast gradient technology. Emerging clinical applications of 7-T MRI and state-of-the-art gradient systems equipped with up to 300 mT/m gradient strength are reviewed, and the impact and benefits of such advances to anatomical, structural and functional MRI are discussed in a variety of neurological conditions. Finally, an outlook and future directions for ultrahigh field MRI combined with ultrahigh and ultrafast gradient technology in neuroimaging are examined.

Tuned neural responses to haptic numerosity in the putamen

The ability to perceive the numerosity of items in the environment is critical for behavior of species across the evolutionary tree. Though the focus of studies of numerosity perception lays on the parietal and frontal cortices, the ability to perceive numerosity by a range of species suggests that subcortical nuclei may be implicated in the process. Recently, we have uncovered tuned neural responses to haptic numerosity in the human cortex. Here, we questioned whether subcortical nuclei are also engaged in perception of haptic numerosity. To that end, we utilized a task of haptic numerosity exploration, together with population receptive field model of numerosity selective responses measured at ultra-high field MRI (7T). We found tuned neural responses to haptic numerosity in the bilateral putamen. Similar to the cortex, the population receptive fields tuning width increased with numerosity. The tuned responses to numerosity in the putamen extend its role in cognition and propose that the motor-sensory loops of the putamen and basal ganglia might take an active part in numerosity perception and preparation for future action.

Clarifying the role of higher-level cortices in resolving perceptual ambiguity using ultra high field fMRI

The brain is organized into distinct, flexible networks. Within these networks, cognitive variables such as attention can modulate sensory representations in accordance with moment-to-moment behavioral requirements. These modulations can be studied by varying task demands; however, the tasks employed are often incongruent with the postulated functions of a sensory system, limiting the characterization of the system in relation to natural behaviors. Here we combine domain-specific task manipulations and ultra-high field fMRI to study the nature of top-down modulations. We exploited faces, a visual category underpinned by a complex cortical network, and instructed participants to perform either a stimulus-relevant/domain-specific or a stimulus-irrelevant task in the scanner. We found that 1. perceptual ambiguity (i.e. difficulty of achieving a stable percept) is encoded in top-down modulations from higher-level cortices; 2. the right inferior-temporal lobe is active under challenging conditions and uniquely encodes trial-by-trial variability in face perception.

Tailored haemodynamic response function increases detection power of fMRI in awake dogs (Canis familiaris)

Functional magnetic resonance imaging (fMRI) of awake and unrestrained dogs (Canis familiaris) has been established as a novel opportunity for comparative neuroimaging, promising important insights into the evolutionary roots of human brain function and cognition. However, data processing and analysis pipelines are often derivatives of methodological standards developed for human neuroimaging, which may be problematic due to profound neurophysiological and anatomical differences between humans and dogs. Here, we explore whether dog fMRI studies would benefit from a tailored dog haemodynamic response function (HRF). In two independent experiments, dogs were presented with different visual stimuli. BOLD signal changes in the visual cortex during these experiments were used for (a) the identification and estimation of a tailored dog HRF, and (b) the independent validation of the resulting dog HRF estimate. Time course analyses revealed that the BOLD signal in the primary visual cortex peaked significantly earlier in dogs compared to humans, while being comparable in shape. Deriving a tailored dog HRF significantly improved the model fit in both experiments, compared to the canonical HRF used in human fMRI. Using the dog HRF yielded significantly increased activation during visual stimulation, extending from the occipital lobe to the caudal parietal cortex, the bilateral temporal cortex, into bilateral hippocampal and thalamic regions. In sum, our findings provide robust evidence for an earlier onset of the dog HRF in two visual stimulation paradigms, and suggest that using such an HRF will be important to increase fMRI detection power in canine neuroimaging. By providing the parameters of the tailored dog HRF and related code, we encourage and enable other researchers to validate whether our findings generalize to other sensory modalities and experimental paradigms.

Hemodynamic response varies across tactile stimuli with different temporal structures

Tactile stimuli can be distinguished based on their temporal features (e.g., duration, local frequency, and number of pulses), which are fundamental for vibrotactile frequency perception. Characterizing how the hemodynamic response changes in shape across experimental conditions is important for designing and interpreting fMRI studies on tactile information processing. In this study, we focused on periodic tactile stimuli with different temporal structures and explored the hemodynamic response function (HRF) induced by these stimuli. We found that HRFs were stimulus‐dependent in tactile‐related brain areas. Continuous stimuli induced a greater area of activation and a stronger and narrower hemodynamic response than intermittent stimuli with the same duration. The magnitude of the HRF increased with increasing stimulus duration. By normalizing the characteristics into topographic matrix, nonlinearity was obvious. These results suggested that stimulation patterns and duration within a cycle may be key characters for distinguishing different stimuli. We conclude that different temporal structures of tactile stimuli induced different HRFs, which are essential for vibrotactile perception and should be considered in fMRI experimental designs and analyses.

New acquisition techniques and their prospects for the achievable resolution of fMRI

This work reviews recent advances in technologies for functional magnetic resonance imaging (fMRI) of the human brain and highlights the push for higher functional specificity based on increased spatial resolution and specific MR contrasts to reveal previously undetectable functional properties of small-scale cortical structures. We discuss how the combination of MR hardware, advanced acquisition techniques and various MR contrast mechanisms have enabled recent progress in functional neuroimaging. However, these advanced fMRI practices have only been applied to a handful of neuroscience questions to date, with the majority of the neuroscience community still using conventional imaging techniques. We thus discuss upcoming challenges and possibilities for fMRI technology development in human neuroscience. We hope that readers interested in functional brain imaging acquire an understanding of current and novel developments and potential future applications, even if they don't have a background in MR physics or engineering. We summarize the capabilities of standard fMRI acquisition schemes with pointers to relevant literature and comprehensive reviews and introduce more recent developments.

Ultra-high spatial resolution BOLD fMRI in humans using combined segmented-accelerated VFA-FLEET with a recursive RF pulse design

PURPOSE

To alleviate the spatial encoding limitations of single-shot echo-planar imaging (EPI) by developing multi-shot segmented EPI for ultra-high-resolution functional MRI (fMRI) with reduced ghosting artifacts from subject motion and respiration.

THEORY AND METHODS

Segmented EPI can reduce readout duration and reduce acceleration factors, however, the time elapsed between segment acquisitions (on the order of seconds) can result in intermittent ghosting, limiting its use for fMRI. Here, "FLEET" segment ordering, where segments are looped over before slices, was combined with a variable flip angle progression (VFA-FLEET) to improve inter-segment fidelity and maximize signal for fMRI. Scaling a sinc pulse's flip angle for each segment (VFA-FLEET-Sinc) produced inconsistent slice profiles and ghosting, therefore, a recursive Shinnar-Le Roux (SLR) radiofrequency (RF) pulse design was developed (VFA-FLEET-SLR) to generate unique pulses for every segment that together produce consistent slice profiles and signals.

RESULTS

The temporal stability of VFA-FLEET-SLR was compared against conventional-segmented EPI and VFA-FLEET-Sinc at 3T and 7T. VFA-FLEET-SLR showed reductions in both intermittent and stable ghosting compared to conventional-segmented and VFA-FLEET-Sinc, resulting in improved image quality with a minor trade-off in temporal SNR. Combining VFA-FLEET-SLR with acceleration, we achieved a 0.6-mm isotropic acquisition at 7T, without zoomed imaging or partial Fourier, demonstrating reliable detection of blood oxygenation level-dependent (BOLD) responses to a visual stimulus. To counteract the increased repetition time from segmentation, simultaneous multi-slice VFA-FLEET-SLR was demonstrated using RF-encoded controlled aliasing.

CONCLUSIONS

VFA-FLEET with a recursive RF pulse design supports acquisitions with low levels of artifact and spatial blur, enabling fMRI at previously inaccessible spatial resolutions with a "full-brain" field of view.

Robust functional mapping of layer-selective responses in human lateral geniculate nucleus with high-resolution 7T fMRI

The lateral geniculate nucleus (LGN) of the thalamus is the major subcortical relay of retinal input to the visual cortex. It plays important roles in visual perception and cognition and is closely related with several eye diseases and brain disorders. Primate LGNs mainly consist of six layers of monocular neurons with distinct cell types and functions. The non-invasive measure of layer-selective activities of the human LGN would have broad scientific and clinical implications. Using high-resolution functional magnetic resonance imaging (fMRI) at 7 Tesla (T) and carefully designed visual stimuli, we achieved robust functional mapping of eye-specific and also magnocellular/parvocellular-specific laminar patterns of the human LGN. These laminar patterns were highly reproducible with different pulse sequences scanned on separate days, between different subjects, and were in remarkable consistency with the simulation from high-resolution histology of the human LGNs. These findings clearly demonstrate that 7T fMRI can robustly resolve layer-specific responses of the human LGN. This paves the way for future investigation of the critical roles of the LGN in human visual perception and cognition, as well as the neural mechanisms of many developmental and neurodegenerative diseases.

Measurement of ultra-fast signal progression related to face processing by 7T fMRI

Given that the brain is a dynamic system, the temporal characteristics of brain function are important. Previous functional magnetic resonance imaging (fMRI) studies have attempted to overcome the limitations of temporal resolution to investigate dynamic states of brain activity. However, finding an fMRI method with sufficient temporal resolution to keep up with the progress of neuronal signals in the brain is challenging. This study aimed to detect between‐hemisphere signal progression, occurring on a timescale of tens of milliseconds, in the ventral brain regions involved in face processing. To this end, we devised an inter‐stimulus interval (ISI) stimulation scheme and used a 7T MRI system to obtain fMRI signals with a high signal‐to‐noise ratio. We conducted two experiments: one to measure signal suppression depending on the ISI and another to measure the relationship between the amount of suppression and the ISI. These two experiments enabled us to measure the signal transfer time from a brain region in the ventral visual stream to its counterpart in the opposite hemisphere through the corpus callosum. These findings demonstrate the feasibility of using fMRI to measure ultra‐fast signals (tens of milliseconds) and could facilitate the elucidation of further aspects of dynamic brain function.

Model-based physiological noise removal in fast fMRI

Recent improvements in the speed and sensitivity of fMRI acquisition techniques suggest that fast fMRI can be used to detect and precisely localize sub-second neural dynamics. This enhanced temporal resolution has enormous potential for neuroscientists. However, physiological noise poses a major challenge for the analysis of fast fMRI data. Physiological noise scales with sensitivity, and its autocorrelation structure is altered in rapidly sampled data, suggesting that new approaches are needed for physiological noise removal in fast fMRI. Existing strategies either rely on external physiological recordings, which can be noisy or difficult to collect, or employ data-driven approaches which make assumptions that may not hold true in fast fMRI. We created a statistical model of harmonic regression with autoregressive noise (HRAN) to estimate and remove cardiac and respiratory noise from the fMRI signal directly. This technique exploits the fact that cardiac and respiratory noise signals are fully sampled (rather than aliasing) when imaging at fast rates, allowing us to track and model physiology over time without requiring external physiological measurements. We then created a joint model of neural hemodynamics, and physiological and autocorrelated noise to more accurately remove noise. We first verified that HRAN accurately estimates cardiac and respiratory dynamics and that our model demonstrates goodness-of-fit in fast fMRI data. In task-driven data, we then demonstrated that HRAN is able to remove physiological noise while leaving the neural signal intact, thereby increasing detection of task-driven voxels. Finally, we established that in both simulations and fast fMRI data HRAN is able to improve statistical inferences as compared with gold-standard physiological noise removal techniques. In conclusion, we created a tool that harnesses the novel information in fast fMRI to remove physiological noise, enabling broader use of the technology to study human brain function.

Differential cortical activation during the perception of moving objects along different trajectories

Detection of 3D object-motion trajectories depends on the integration of two distinct visual cues: translational displacement and looming. Electrophysiological studies have identified distinct neuronal populations, whose activity depends on the precise motion cues present in the stimulus. This distinction, however, has been less clear in humans, and it is confounded by differences in the behavioral task being performed. We analyzed whole-brain fMRI, while subjects performed a common time-to-arrival task for objects moving along three trajectories: moving directly towards the observer (collision course), with trajectories parallel to the line of sight (passage course), and with trajectories perpendicular to the line of sight (gap closure). We found that there was substantial overlap in the pattern of activation associated with each of the three tasks, with differences among conditions limited to the human motion area (hMT+), which showed greater activation extent in the gap closure condition than for either collision or passage courses. These results support a common substrate for temporal judgments of an object's time-to-arrival, wherein the special cases of object motion directly toward, or perpendicular to, the observer represent two extremes within the broader continuum of 3D passage trajectories relative to the observer.

Differential Effects of Sustained Manual Pressure Stimulation According to Site of Action

Sustained pressure stimulation of the body surface has been used in several physiotherapeutic techniques, such as reflex locomotion therapy. Clinical observations of global motor responses and subsequent motor behavioral changes after stimulation in certain sites suggest modulation of central sensorimotor control, however, the neuroanatomical correlates remain undescribed. We hypothesized that different body sites would specifically influence the sensorimotor system during the stimulation. We tested the hypothesis using functional magnetic resonance imaging (fMRI) in thirty healthy volunteers (mean age 24.2) scanned twice during intermittent manual pressure stimulation, once at the right lateral heel according to reflex locomotion therapy, and once at the right lateral ankle (control site). A flexible modeling approach with finite impulse response basis functions was employed since non-canonical hemodynamic response was expected. Subsequently, a clustering algorithm was used to separate areas with differential timecourses. Stimulation at both sites induced responses throughout the sensorimotor system that could be mostly separated into two anti-correlated subsystems with transient positive or negative signal change and rapid adaptation, although in heel stimulation, insulo-opercular cortices and pons showed sustained activation. In direct voxel-wise comparison, heel stimulation was associated with significantly higher activation levels in the contralateral primary motor cortex and decreased activation in the posterior parietal cortex. Thus, we demonstrate that the manual pressure stimulation affects multiple brain structures involved in motor control and the choice of stimulation site impacts the shape and amplitude of the blood oxygenation level-dependent response. We further discuss the relationship between the affected structures and behavioral changes after reflex locomotion therapy.

Gastric stimulation drives fast BOLD responses of neural origin

Functional magnetic resonance imaging (fMRI) is commonly thought to be too slow to capture any neural dynamics faster than 0.1 Hz. However, recent findings demonstrate the feasibility of detecting fMRI activity at higher frequencies beyond 0.2 Hz. The origin, reliability, and generalizability of fast fMRI responses are still under debate and await confirmation through animal experiments with fMRI and invasive electrophysiology. Here, we acquired single-echo and multi-echo fMRI, as well as local field potentials, from anesthetized rat brains given gastric electrical stimulation modulated at 0.2, 0.4 and 0.8 Hz. Such gastric stimuli could drive widespread fMRI responses at corresponding frequencies from the somatosensory and cingulate cortices. Such fast fMRI responses were linearly dependent on echo times and thus indicative of blood oxygenation level dependent nature (BOLD). Local field potentials recorded during the same gastric stimuli revealed transient and phase-locked broadband neural responses, preceding the fMRI responses by as short as 0.5 s. Taken together, these results suggest that gastric stimulation can drive widespread and rapid fMRI responses of BOLD and neural origin, lending support to the feasibility of using fMRI to detect rapid changes in neural activity up to 0.8 Hz under visceral stimulation.

On the analysis of rapidly sampled fMRI data

Recent advances in parallel imaging and simultaneous multi-slice techniques have permitted whole-brain fMRI acquisitions at sub-second sampling intervals, without significantly sacrificing the spatial coverage and resolution. Apart from probing brain function at finer temporal scales, faster sampling rates may potentially lead to enhanced functional sensitivity, owing possibly to both cleaner neural representations (due to less aliased physiological noise) and additional statistical benefits (due to more degrees of freedom for a fixed scan duration). Accompanying these intriguing aspects of fast acquisitions, however, confusion has also arisen regarding (1) how to preprocess/analyze these fast fMRI data, and (2) what exactly is the extent of benefits with fast acquisitions, i.e., how fast is fast enough for a specific research aim? The first question is motivated by the altered spectral distribution and noise characteristics at short sampling intervals, while the second question seeks to reconcile the complicated trade-offs between the functional contrast-to-noise ratio and the effective degrees of freedom. Although there have been recent efforts to empirically approach different aspects of these two questions, in this work we discuss, from a theoretical perspective accompanied by some illustrative, proof-of-concept experimental in vivo human fMRI data, a few considerations that are rarely mentioned, yet are important for both preprocessing and optimizing statistical inferences for studies that employ acquisitions with sub-second sampling intervals. Several summary recommendations include concerns regarding advisability of relying on low-pass filtering to de-noise physiological contributions, employment of statistical models with sufficient complexity to account for the substantially increased serial correlation, and cautions regarding using rapid sampling to enhance functional sensitivity given that different analysis models may associate with distinct trade-offs between contrast-to-noise ratios and the effective degrees of freedom. As an example, we demonstrate that as TR shortens, the intrinsic differences in how noise is accommodated in general linear models and Pearson correlation analyses (assuming Gaussian distributed stochastic signals and noise) can result in quite different outcomes, either gaining or losing statistical power.

The influence of respiration on brainstem and cardiovagal response to auricular vagus nerve stimulation: A multimodal ultrahigh-field (7T) fMRI study

BACKGROUND

Brainstem-focused mechanisms supporting transcutaneous auricular VNS (taVNS) effects are not well understood, particularly in humans. We employed ultrahigh field (7T) fMRI and evaluated the influence of respiratory phase for optimal targeting, applying our respiratory-gated auricular vagal afferent nerve stimulation (RAVANS) technique.

HYPOTHESIS

We proposed that targeting of nucleus tractus solitarii (NTS) and cardiovagal modulation in response to taVNS stimuli would be enhanced when stimulation is delivered during a more receptive state, i.e. exhalation.

METHODS

Brainstem fMRI response to auricular taVNS (cymba conchae) was assessed for stimulation delivered during exhalation (eRAVANS) or inhalation (iRAVANS), while exhalation-gated stimulation over the greater auricular nerve (GANctrl, i.e. earlobe) was included as control. Furthermore, we evaluated cardiovagal response to stimulation by calculating instantaneous HF-HRV from cardiac data recorded during fMRI.

RESULTS

Our findings demonstrated that eRAVANS evoked fMRI signal increase in ipsilateral pontomedullary junction in a cluster including purported NTS. Brainstem response to GANctrl localized a partially-overlapping cluster, more ventrolateral, consistent with spinal trigeminal nucleus. A region-of-interest analysis also found eRAVANS activation in monoaminergic source nuclei including locus coeruleus (LC, noradrenergic) and both dorsal and median raphe (serotonergic) nuclei. Response to eRAVANS was significantly greater than iRAVANS for all nuclei, and greater than GANctrl in LC and raphe nuclei. Furthermore, eRAVANS, but not iRAVANS, enhanced cardiovagal modulation, confirming enhanced eRAVANS response on both central and peripheral neurophysiological levels.

CONCLUSION

7T fMRI localized brainstem response to taVNS, linked such response with autonomic outflow, and demonstrated that taVNS applied during exhalation enhanced NTS targeting.